A Novel Vehicle Detection Framework Based on Parallel Vision

Autonomous driving has become a prevalent research topic in recent years, arousing the attention of many academic universities and commercial companies. As human drivers rely on visual information to discern road conditions and make driving decisions, autonomous driving calls for vision systems such as vehicle detection models. These vision models require a large amount of labeled data while collecting and annotating the real traffic data are time-consuming and costly. Therefore, we present a novel vehicle detection framework based on the parallel vision to tackle the above issue, using the specially designed virtual data to help train the vehicle detection model. We also propose a method to construct large-scale artificial scenes and generate the virtual data for the vision-based autonomous driving schemes. Experimental results verify the effectiveness of our proposed framework, demonstrating that the combination of virtual and real data has better performance for training the vehicle detection model than the only use of real data.

Persepsi Siswa dan Guru terhadap Penggunaan Laboratorium Virtual dalam Pembelajaran Fisika

Sampai saat ini Pandemi masih belum berakhir, upaya demi upaya terus dilakukan oleh pemerintah dan juga semua lapisan masyarakat untuk bisa menghentikan rantai penyebaran Covid 19 ini. Selama hampir 2 tahun Covid 19 membesamai kita, tentunya banyak sekali dampak yang dirasakan. Pendidikan merupakan salah satu bidang yang sangat terdampak dengan adanya Covid 19 ini. Kegiatan belajar mengajar seketika diberhentikan dan dialihkan Menjadi sistem belajar online. Tidak mudah untuk sebagian orang atau lembaga untuk menyesuaikan sistem pembelajaran dengan keadaan. Namun disamping itu teknologi berkembang dengan sangat pesat, masyarakat pun mulai beradaptasi dengan keadaan dan mulai mengembangkan, memanfaatkan teknologi yang ada. Dalam pembelajaran fisika contohnya, Metode pembelajaran saintifik dan juga prosedur kerja ilmiah yang seharusnya dilakukan secara langsung kini mulai dilakukan secara online juga. Laboratorium virtual menjadi salah satu alternatif untuk bisa melaksanakan praktikum sesuai dengan materi ajar yang diberikan. Banyak pro dan kontra yang terjadi di masyarakat mengenai penggunaan Laboratorium Virtual ini, terlebih mereka yang masih kekurangan fasilitas dan proses akses internet yang kurang terjangkau. Penelitian ini bertujuan untuk menggali dan mengkaji respon komponen pendidikan seperti siswa dan guru dalam Penggunaan Laboratorium Virtual di sekolah. Sehingga memberikan gambaran nyata sebagai acuan untuk pemilihan solusi bagi lapisan masyarakat yang paling terdampak akibat pandemik. Penelitian yang digunakan adalah penelitian kualitatif deskriptif. Penelitian ini menggunakan teknik pengumpulan data sekunder, Dengan instrumen penyebaran angket online kepada siswa dan guru fisika di tingkat SMA sampai universitas, Dengan topik pertanyaan penggunaan laboratorium virtual. Data hasil survei digunakan sebagai acuan untuk mencari solusi dari permasalahan metode pembelajaran dan praktikum fisika di era Pandemi.

Virtual Data Repository Stimulates Data Sharing in a Consortium

Research data may have substantial impact beyond the original study objectives. The Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO) facilitates the combination of data and access to specimens from nine NIDA-funded cohorts in a virtual data repository (VDR). Unique challenges were addressed to create the VDR. An initial set of common data elements was agreed upon, selected based on their importance for a wide range of research proposals. Data were mapped to a common set of values. Bioethics consultations resulted in the development of various controls and procedures to protect against inadvertent disclosure of personally identifiable information. Standard operating procedures govern the evaluation of proposed concepts, and specimen and data use agreements ensure proper data handling and storage. Data from eight cohorts have been loaded into a relational database with tables capturing substance use, available specimens, and other participant data. A total of 6,177 participants were seen at a study visit within the past six months and are considered under active follow-up for C3PNO cohort participation as of the third data transfer, which occurred in January 2020. A total of 70,391 biospecimens of various types are available for these participants to test approved scientific hypotheses. Sociodemographic and clinical data accompany these samples. The VDR is a web-based interactive, searchable database available in the public domain, accessed at www.c3pno.org. The VDR are available to inform both consortium and external investigators interested in submitting concept sheets to address novel scientific questions to address high priority research on HIV/AIDS in the context of substance use. Keywords: common data elements, data repository Abbreviations: National Institute on Drug Abuse (NIDA), Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO), human immunodeficiency virus (HIV), acquired immunodeficiency syndrome (AIDS), injecting drug users (IDU), virtual data repository (VDR) Correspondence: [email protected]*

КЛЮЧОВІ УМОВИ ТА ХАРАКТЕРИСТИКИ ФОРМУВАННЯ ДОПОВНЕНОЇ РЕАЛЬНОСТІ

The purpose of the study is to highlight the key conditions of the design of a multimedia system, which are created an augmented reality. The research methodology is based on the use of general scientific methods. The analysis of scientific papers on the topic and the analysis of multimedia which are using like AR projects technologies are aimed at determining the features of augmented reality formation. Results.With the advent of a wide variety of multimedia projects, it is not always clear which of them belong to augmented reality. Some multimedia use only similar technologies, such as projections, but there is no question of augmented reality. On the example of simple and visual projections, as well as other projects, consider at what point the phenomenon of augmented reality occurs. The analysis of publications that consider the augmented reality and determine the place of augmented reality in various continuums is carried out. Has been determined the conditions for the AR formation as a phenomenon. We discuss the importance of the simultaneous presence of virtual data, narrative, and context. There were also indicated the significance of the relevance of virtual data for AR, the indirect influence of interactivity on the context, and the difference between the essence of augmented reality and ordinary digital modification. Various cases of optical and video mixing are considered conventional and 3D projections, 3D mapping, augmented images. It has been proven that the formation of a narrative is a prerequisite for creating augmented reality and the connection between virtual data and context. The scientific novelty of the work consists in in determining the conditions for the formation of the augmented reality and their characteristics. The practical significance of the results lies in the fact that the verification of compliance with the conditions and characteristics helps to separate augmented reality projects from other types of multimedia and other uses of similar technologies.

Analysis of Psychological and Emotional Tendency Based on Brain Functional Imaging and Deep Learning

When facing various pressures, human beings will have different degrees of bad psychological emotions, especially depression and anxiety. How to effectively obtain psychological data signals and use advanced intelligent technology to identify and make decisions is a research hotspot in psychology and computer science. Therefore, a personal emotional tendency analysis method based on brain functional imaging and deep learning is proposed. Firstly, the EEG forward model is established according to functional magnetic resonance imaging (fMRI), and the transfer matrix from the signal source at the cerebral cortex to the head surface electrode is obtained. Therefore, the activation results of fMRI emotional experiment can be mapped to the three-layer head model to obtain the EEG topographic map reflecting the degree of emotional correlation. Then, combining data enhancement (Mixup) with three-dimensional convolutional neural network (3D-CNN), an emotion-related EEG topographic map classification method based on M-3DCNN is proposed. Mixup is used to generate virtual data, the original data and virtual data are used to train the network together, the number of training samples is expanded, the overfitting phenomenon of 3D-CNN is alleviated, and 3D-CNN is used for feature extraction and classification. Experimental data analysis shows that, compared with traditional methods, the proposed method can retain emotion related EEG signals to a greater extent and obtain a higher accuracy of emotion five classifications under the same feature dimension.

An ABAQUS® plug-in for generating virtual data required for inverse analysis of unidirectional composites using artificial neural networks

This paper presents a robust ABAQUS® plug-in called Virtual Data Generator (VDGen) for generating virtual data for identifying the uncertain material properties in unidirectional lamina through artificial neural networks (ANNs). The plug-in supports the 3D finite element models of unit cells with square and hexagonal fibre arrays, uses Latin-Hypercube sampling methods and robustly imposes periodic boundary conditions. Using the data generated from the plug-in, ANN is demonstrated to explicitly and accurately parameterise the relationship between fibre mechanical properties and fibre/matrix interphase parameters at microscale and the mechanical properties of a UD lamina at macroscale. The plug-in tool is applicable to general unidirectional lamina and enables easy establishment of high-fidelity micromechanical finite element models with identified material properties.

An openEHR Virtual Patient Template for Pancreatic Cancer

openEHR is an open-source technology for e-health, aims to build data models for interoperable Electronic Health Records (EHRs) and to enhance semantic interoperability. openEHR architecture consists of different building blocks, among them is the “template” which consists of different archetypes and aims to collect the data for a specific use-case. In this paper, we created a generic data model for a virtual pancreatic cancer patient, using the openEHR approach and tools, to be used for testing and virtual environments. The data elements for this template were derived from the “Oncology minimal data set” of HiGHmed project. In addition, we generated virtual data profiles for 10 patients using the template. The objective of this exercise is to provide a data model and virtual data profiles for testing and experimenting scenarios within the openEHR environment. Both of the template and the 10 virtual patient profiles are available publicly.